Where's Waldo: Antarctica #1

Waldo (the ROW warm trend) is not in Africa (or the United States). Is Waldo in Antarctica? (For those of you who haven’t bought toys in 30 years, Where’s Waldo is a game.)

Antarctica is about 8.9% of the world’s land surface (about 1.5 times the contiguous 48). There are 116 Antarctica sites in the GISS data set, of which 48 are classified as “urban” in Peterson et al 2007. (Just joking). They are all GISS-rural. Since a particular interest is how 1934 compares to 1998, I selected all the sites with records that go back to 1930 and extend past 1990, yielding the remarkable results shown below, which was undoubtedly one of the major reasons why Hansen and Schmidt were so confident of relative temperatures between the 1930s and the present.

90 Comments

Since a particular interest is how 1934 compares to 1998, I selected all the sites with records that go back to 1930 and extend past 1990, yielding the remarkable results shown below, which was undoubtedly one of the major reasons why Hansen and Schmidt were so confident of relative temperatures between the 1930s and the present.

If you want to see a bad track record, just look at the bad track record Hansen et al have for teasing readers with mythical data records and methodologies in support of climate cult religion…err science (cough, cough).

*sigh* Guess I’m not worthy, nor enlightened enough to see the remarkable results Steve speaks of. Does this mean I’m consigned to the rank of ‘Jester’? I so much prefer the title ‘Denier’. What do I have to do to reach the exalted rank of ‘Denier’?

They have a posited a system with positive feedbacks and TIME CONSTANTS on the order
of decades.

And they propose a system that has huge inertia. A system that will continue on path
long after control inputs are applied. I predict OVERSHOOT.

And they Propose control methods. A C02 Limiter.

And they are “closing the loop” by looking at the noisiest, peice of junk, output.
Temperature.

Essentially, from a contrl standpoint, they propose a CO2 limiter. These controls
may be effective within the propsed time constant of the system. HOWEVER in the short
term people will observe the noisy signal of temp. And it will lead to confusion.
and PIO.

Come on guys! Everyone knows that there is no warming in the Southern Hemisphere! CO2 is a gas that is lighter than air and it rises in the atmosphere. And since the Earth is oriented UP its all in the Northern Hemisphere! Once there it combines with second hand smoke to create a plasma jet that is slowly rotating the earth into a DOWN position where the gases will then rise to the South pole. Gosh

The IPCC in the AR4 now ignores Antarctica (unlike in the TAR where their models got the predictions wrong).
See the Regional Summary on Antarctica (lower left under Regional Summaries) including South Pole CO2 readings.
An inconvenient area of the globe for sure!

From the Understanding and Attributing Climate Change, Executive Summary from the latest (AR4) of the IPCC :

“It is likely that there has been a substantial anthropogenic contribution to surface temperature increases in every continent except Antarctica since the middle of the 20thcentury. Anthropogenic influence has been detected in every continent except Antarctica (which has insufficient observational coverage to make an assessment),”

Antartica is the one place where UHI effectis are almost certainly absent. Is the coverage of Antartica really so sparse and short in history?

Don.W,
That sounds like something Calvin’s father would have said in an attempt to explain something he didn’t feel like going into detail over (uh, Calvin and Hobbes, reminiscent of his father’s explanation for why the sky is blue).

We know exactly where Waldo is – the Arctic. Hansen has even said it himself, which is why he was so confident that US stations didn’t matter. It’s not global warming, it’s arctic warming. But why does the GISS arctic data look so different to Polyakov’s data?

Isn’t Antarctica thermally insulated (that is probably the wrong phrase to use); I mean don’t the ocean and air currents isolate it to a great extent and therefore would we not expect its temperature to remain roughly constant (not over longer timescales but over the kinds of timescale we are interested in here)?

…CO2 is a gas that is lighter than air and it rises in the atmosphere. And since the Earth is oriented UP its all in the Northern Hemisphere!…

Insightful, but not quite correct. Actually, the mercury is rising at both poles, after you apply necessary adjustments.

Thermometers are linear (Euclidean) devices; the earth is spherical. Once NASA converts the linear thermometer data — a complex transformation from spherical to Euclidean coordinate systems (“mercury rising” at the South Pole actually goes down; let Calvin think about that for a while!) — and apply other corrections and adjustments, mercury is found to be rising everywhere.

re 2 & 3
I suspect what WFR means is that he can’t see the graphs – and nor can I. I can’t see anything beyond paragraph 2. And the comments aren’t wrapping properly – they disappear off the screen when they get to the end of the comment box. I’m using IE6 (at work, so can’t do anything about that).

Unless the temperature sensors are a significant distance from the research outposts, I believe that there is a good chance that the UHI in Antartica is not zero.
Probably only a few tenths of a degree, but not zero.
Especially given the size of the measured UHI in Barrow, Alaska.

#32 Suddenly Mr Lindstroem is the “serious” guy
in a thread… Leonard! Take a look on photos
of Faraday etc… Esperanza is quite a village with
“Falu-red” houses with black roofs, all this on
black gravel…UHI IS not to be taken as a certain
Gavin does in some way, yesterday in unthreaded if
I’m not mistaken (Vernon relating a RC discussion),
litterally, just one (1) house can increase the
temperature 1C, mostly a little less, I think
we need more research on UHI, but check the
Barrow winter UHI study for a start, Barrow Alaska,
GWS…

Mr. McIntyre – It seems that you are choosing parts of the world with admittedly sparse coverage and implying that this is indicative of the situation in the ROW. The 2007 IPCC report in Chapter 3 clearly indicates that gaps in coverage in the tropics, Southern Hemisphere, and Antarctica are substantial. It would be more appropriate for you to state that this is what has already been concluded and you are simply repeating that which is already known. Why don’t you look at the land data for rural stations in India, Asia, Russia, Australia, and Europe? Also, why are you focusing on just the land station data? If the GISS temperature data is so contrived, then why are the combined land-ocean surface data and the satellite data for the lower troposphere consistent?

In this context, I’m responding to comments from SChmidt and Hansen which say that the U.S. is a negligible proportion of the world’s land surface in order to support their view that errors don’t matter.

What I’m trying to assess is what proportion the U.S. constitutes of the world’s land surface for which meaningful comparisons can be drawn between the 1930s and the present. My guess is that it’s larger than 6% and possibly much larger as some of the land surface invoked by Schmidt and Hansen in their comparison has no usable information. Perhaps IPCC 2007 also said this, but then the obligation lay on Schmidt and Hansen to make a more measured statement.

However, if Hansen and Schmidt had said that the U.S. constitutes only (say) 30% of the land surface for which there are meaningful comparisons between the 1930s and the present and therefore U.S. errors don’t matter, the words might not have rolled off their tongues so easily.

I’ve posted on Russia and China in the past – see about 5-6 months ago – in connection with Jones et al 1990 and those observations by and large still apply here.

I hadn’t looked previously at exactly what information was available in Africa or Antarctica or South America I like to examine things first-hand. In addition, because Hansen won’r release his exact code, if I’m going to try to benchmark his calculations, it’s easier to start with areas with relatively few stations.

As to the satellite data, I’m unaware of any records that would permit direct comparison between the 1930s and the present and would welcome any links to this data that you can provide.

As to the SST data, I have posted on the bucket adjustments which are very problematic.

Having said all this, I’ve always made it quite clear that I think that the conventional temperature history is fairly plausible for the past 150 years but I’d like to see exactly what is known and what isn’t known.

I am not picking on anyone, just stating facts in the spirit of Donald Rumsfeld.

Reports that say that something hasnt happened are always interesting to me because, as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we dont know.

I caught the reference. I was referring to the Plain English Campaign group who gave him an award for making “the most baffling quote” by a public figure…and apparently can’t read plain English. My understanding was that at least one member of the award committee was an English Professor from Oxford, but after a quick search, I can’t confirm that.

All in all, there are 7,086,372 monthly observations in the GHCN. Of these, 365,755 are missing values. Fully 2,244,733 non-missing monthly mean temperatures are from U.S. stations. That is, about a third of the data in the GHCN is from the U.S.

RE: #22 – I’ll raise you one unintended consequence. From a deep earth history perspective, we remain dangerously close to the to-date historic CO2 low point. People worry about some pending extinction, however, I point out that there has already been an ongoing massive one. Namely, an entire assemblage of pre Tertiary life is gone forever with only the most limited scattered remnents still in existence. Now, let me describe, in the tradition of Erwin et al, a highly telling hopeful monster. The Coast Live Oak. This hopeful monster is my own personal archetype for the cold, dry era we are in. An era that is CO2 limited, innately, due to how low PP(CO2) in the atmosphere is. If, some day, you see my hopeful monster becoming extinct, you better have a good galactic life boat ready to sail. Because, it will mean one of two things. Either PP(CO2) has gone below the critical point naturally, or, we’ve done it to ourselves.

#42 Sinan,
For the GISS, there is no rural station in France that has data after 1990. I don’t see any reason why a station with consitent records like Mont Aigoual (it can’t be more rural and better followed) is not included by the GISS, apart from the fact that its temperature is not consitent with the GHG theory (a sudden jump in the 1980s then a stasis for more than 10 years): graph here

Re: 41 89034 Belgrano Clear discontinuity upward in ca 1967.
89066 Base San Mart Possible slight uptrend in maxs, clear uptrend in mins 1975 to 2007
Vostok Warming of maxs to ca 1980, cooling to 1990, then flat??. Mins are off scale
all others – no trend. Note: plots are in tenths of a degree.
Re: 50 Thank you, thank you. I have posted the observation twice that USA represents 20% of stations if only 2% of land area. Seems to me that the USA weights the result far out of proportion to land area.
Murray

Steve – Thanks for the response. I did not mean to imply that satellite temperature data exists for that long ago. Rather that during the time period for which satellite data exists, the satellite data are consistent with the combined land-ocean surface data. I understand why you are looking at historical data for comparison between 1930’s temperature data and recent data, but I’m not sure why you are focusing on regions of the world with poor station coverage. While the number and history of stations in the US may make the US temperature record more reliable than in other parts of the world, it does not contribute as large a proportion to the trends in the GHCN data (as suggested by #49) due to gridding of the temperature data. What might be more worthwhile to check is the validity of the interpolation of missing data in the temperature record and the relative errors introduced by such interpolation. Wouldn’t that give a better idea as to whether or not Hansen’s and Schmidt’s comments are valid or not?

Re38
Must be missing something. I was taught in school that Mercury is a metal which will vaporizes at high temperatures and is fluid until it solidifies at -38C [-39F]. Therefore mercury-based thermometers are useless in any area likely to experience extreme low temperatures, of course including the Arctic and Antarctica. Thermometers for these areas are alcohol-based.

#58. I was just teasing with the satellite remark. Isn’t the degree of reconciliation between surface and satellite still somewhat in the eye of the beholder – I say this, but don’t have time to do a proper reconciliation of the current situation right now and therefore can’t debate it.

Does such matching between present records mean that Hansen’s calculation of African temperatures in the 1930s is valid? I don’t think so. To get there, you have to see what Hansen did. If he disclosed his source code, one could assess matters fairly directly. But since he hasn’t disclosed his source code, the only approach that I know of is to examine the available data sets, adjusted and unadjusted, and then look at the cursory descriptions in his articles and try to guess how one can get from A to B. To do this, you have to start with “simple” areas, like Africa or South America and then try to build on an algorithm to reconstruct China or Russia or Europe. If it seems a little sadistic exposing what Hansen did, well, it’s still what he did.

BTW if the data is bad, I don’t think that that means that it’s unusable or that no conclusions can possibly result. It’s just that you have to sift through the data and properly examine the meta data and see exactly what you can conclude. PArt of the problem in this area is the lack of Technical Reports, where authors describe the exact problems with the record at Isla Huafo or whatever and a little less time philosophizing about the destruction of Creation.

As to the “gridding” – at the end of the day, any gridding algorithm is just yielding a weighted average of the original data. I don’t see any step in Hansen which is not a linear step so all the Wizard of Oz machinations will reduce to the calculation of weighting factors, just like Mann’s did.

There are 1,670 (out of 4,495) WMO station ids in the GHCN v2 which have observations both in the 30s and the 90s. I included in this list any station with at least one observation between 1930 – 1939 inclusive and at least one observation between 1990 – 1999 inclusive.

>> the only approach that I know of is to examine the available data sets, adjusted and unadjusted, and then look at the cursory descriptions in his articles and try to guess how one can get from A to B.

If all you wanted to to was audit Hansen’s claim of “1998 warmest”, yes. But whether 1998 (obviously solar induced) is hotter than 1930 or not is completely irrelevant. Aren’t Hansen and Mann also claiming that there is a dramatic warming trend, ie the hockey stick?

Therefore, it’s certainly more productive to validate or invalidate this claim by comparing averages of surface data to satellite data for a given area to validate surface measurements, and checking the satellite data to see if it looks like a “blade”.

Steve – I find you much more conciliatory than many people have suggested! I wholly agree that the source code should be made available if only for transparency. Minus that though, all of the data is there for anyone with enough time to wade through it and perform their own analyses (such as you are doing). I agree that matching recent data from independent sources does not validate prior data, but it does suggest that the GISS, NCDC, and CRU data analyses are yielding a realistic metric. I have less confidence in that statement for data prior to the 1970’s. Is it best to start with incomplete datasets (such as for Antarctica) in order to determine how the data are adjusted, interpolated, and combined? I would think you would want to start with more complete datasets to eliminate the need for interpolating missing data, then worry about interpolation in sparsely covered regions later.

Let me see if I have this straight.
The satellite record shows a very small warming trend for the last 30 years.
The ground based record shows a much larger warming trend over a much longer period of time.

Therefore, since both the satellite and ground records show warming, the very large warming trend of the ground record must be right?

Minus that though, all of the data is there for anyone with enough time to wade through it and perform their own analyses (such as you are doing).

That’s true for NASA GISS, but not for CRU. I don’t know a) exactly what stations they use; b) what data version is used as input to their gridding; c) whether they’ve transformed their input data – and you need to check these things: any Hansen-type error is undetectable at CRU. That’s probably why they maintain lockdown security on their data.

I would think you would want to start with more complete datasets to eliminate the need for interpolating missing data, then worry about interpolation in sparsely covered regions later.

I’ve looked at USHCN which is one extreme to get a feel for what’s there and Antarctica, South America and Africa at another extreme. I’ve dabbled in China and Russia and Australia. But I’m not really going to spend time on the data-rich areas until I’ve got a solid handle on what Hansen’s doing in “easier” areas. I can assure you that it’s much easier to do methodological detective work in sparse data areas than heavy data areas.

>> I would think you would want to start with more complete datasets to eliminate the need for interpolating missing data

Reading between the lines, by “complete datasets”, I believe you are referring to the satellite data. Am I wrong? If so, I agree with you.

Notice that Steve is completely focused on auditing what Hansen is claiming. The site should be called MannHansenAudit. He only wants to verify the process they went through to reach their conclusions, not validate/invalidate their conclusions.

Let me see if I have this straight.
The satellite record shows a very small warming trend for the last 30 years.
The ground based record shows a much larger warming trend over a much longer period of time.

Therefore, since both the satellite and ground records show warming, the very large warming trend of the ground record must be right?

I don’t think you have it quite straight. The satellite and ground based temperature are in very close agreement over the satellite era (1979 and on). They show the same trend. In fact, for the lower 48 states, SteveM’s discovery brings the surface record into better alignment with the satellite record.
Also, the warming trend for the last 30 years is not small and constitutes most of the modern warming.

I have plotted these results on top of solar activity, and it’s clear that it matches theory, ie solar is driving factor. Especially clear is that the 1998-2003 timeframe is one of extraordinary solar activity.
That’s why I think Hansen’s conclusion is correct! 1998 was the warmest year. It’s already clear from the data that Steve is uncovering that in 1930s, the US warming was not a global phenomena. However, we know from the satellite data that the 1998 peak was global.

There’s always issues of accuracy of measurements as well as their validity and applicability. What does getting the average of air temperature for an area the size of (pick something) tell us? What’s the meaning of it. It helps to know what we’re talking about, correct?

I’m linking to information that explains it an aspect of measuring something using that as an example, sso we don’t have to get into things here. I’m making an observation about how they do things that has links to more specific pages then Steve has in the sidebar and such.

If he considers that discussing it, and my assumption is a mistake I’m sure he’ll make it known and/or delete them and I’ll file that away in my head and adjust.

The only selection criterion I find interesting at this point is based on the condition that a location (identified by the 5 digit WMO number) have observations for both the 30s and the 90s. I want to make use of the monthly nature of the data. I am still thinking about the game plan (as I do not like running multiple specs).

I have a gut reaction against using annual averages (no, I am not going to discuss the reasons here). I don’t like monthly averages much either as a calendar month is an arbitrary boundary. Ideally, I would like to work with seasons defined by the angle of the sun etc.

Thermodynamics in general, especially in a way to try and prove average temperatures don’t exist, I would guess. Sounds rather pointless and circular a type of thing not worth discussing. Plenty of places to do that (or read up on basic science for that matter).

Talking about measuring something and if it tells us anything in the first place is different. That’s what all the measurements are. Samples. Averages. Just stick to mainstream published papers, and keep stuff you’ll read at the sidebared blogs and other resources over there where they’re for that, if it’s not about auditing. I’m sure wikipedia or giss or rc etc would be very helpful for those interested in those subjects. Or a blog about thermodynamics.

Talking about Where’s Waldo and figuring out if what is being said is doing what it’s said to be doing is interesting. Discussions about IR absorbtion and stuff like that are not interesting.

Sorry, I was actually talking to MarkW. Yes, the satellite record picks up 1998’s El Nino a lot more than the surface record. I’d imagine this would be because the satellite tracks the ocean warmth better. I don’t see how solar could be involved as the solar cycle maximum was around 2002–and pretty much the same as 1991.

>> Are you implying that there is something wrong with this? I cant tell.

No, certainly not, just making the destinction. There are implicit logical inferences here, so I think it’s a very useful exercise to make this explicit, because there are a lot of skeptics on this blog that are making an incorrect logical leap. The logical steps are:

Steve M is clearly criticising the Hansen statistical procedure, and thus concluding or implying that the conclusion that 1998 was the warmest year is incorrect. This is resulting in a lot of attention (well deserved). A lot of this attention, though not all, is because it implies that the third part is incorrect.

I’m just noticing that no one on this blog, including Steve, seems very interested in validating whether the conclusion that 1998 was the warmest year or not is actually valid, regardless of deficiencies in Hansen’s methodology. Steve probably wouldn’t get nearly as much attention if he announced:

Hansen’s statistical procedure was flawed, but his conclusion that 1998 was the warmest year is still correct.

I think the data shows that Hansens explicit conclusion is correct! 1998 was the warmest year. We have records from various continents which show that the 1930s warming was not global. Therefore, it was globally cooler than 1998, since we know from satellite data that 1998 was globally warm. We would be intellectually dishonest and no better than Mann and Hansen if we glossed over this fact, just because it’s not the answer some want. We have to follow the evidence where ever it leads.

And for you partisan anti-AGWers out there, it’s a stupid strategy. You are vulnerable to Hansen realizing the same thing, and switching the argument to use what I just said. Then you would lose, since the only argument you have developed is that Hansen’s statistical procedure is flawed.